Surgical workflow monitoring based on trajectory data mining

Authors:
Atsushi Nara;Kiyoshi Izumi;Hiroshi Iseki;Takashi Suzuki;Kyojiro Nambu;Yasuo Sakurai
Affiliations:
Center for Spatial Analysis, University of Oklahoma, Norman, OK;School of Engineering, The University of Tokyo & PRESTO, JST., Bunkyo, Tokyo, Japan;Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Shinjuku-ku, Tokyo, Japan;Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Shinjuku-ku, Tokyo, Japan;Research and Development Center, Toshiba Medical Systems Corporation, Otawara-shi, Tochigi-ken, Japan;Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Shinjuku-ku, Tokyo, Japan
Venue:
JSAI-isAI'10 Proceedings of the 2010 international conference on New Frontiers in Artificial Intelligence
Year:
2010

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Abstract

This research aims at investigating intermediate-scale workflows using the surgical staff's movement pattern. In this study, we have introduced an ultrasonic location aware system to monitor intraoperative movement trajectories on surgical staffs for the workflow analysis. And we developed trajectory data mining for surgical workflow segmentation, and analyzed trajectory data with multiple cases. As a result, in 77.18% of total time, a kind of current operation stage could be correctly estimated. With high accuracy 85.96%, the estimation using trajectory data was able to distinguish whether a current 5 minutes was transition time from one stage to another stage or not.. Based on these results, we are implementing the surgery safe support system that promotes safe & efficient surgical operations.